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Título

ARIN ® procedure for the normalization of multitemporal remote images through vegetative pseudo-invariant features

Autor García Torres, Luis ; Gómez-Candón, David ; Caballero Novella, Juan José
Palabras clave ARIN
Fecha de publicación sep-2013
Citación SPIE Remote Sensing (2013)
ResumenAn Automatic Relative Image Normalization (ARIN®) method was developed to normalize multitemporal remote images based in vegetative pseudo-invariant features (VPIFs), as following: 1) defining the same parcel for each selected VPIF in each multitemporal image; 2) extracting the VIPF spectral bands data for each image; 3) calculating the correction factor (CF) for each image band to fit it to the same expected values, normally for each band the average of the series; 4) obtaining the normalized images by transforming each original image band through the corresponding CF linear functions. ARIN® software was developed to automatically achieve the previously described procedure. We have validated ARIN using a series of six GeoEye-1 satellite images taken over the same Southern of Spain scene in 2010, from early April to October, at about 4 weeks interval. Three VPIFs were chosen: citrus orchards (CIT), riparian trees (POP) and Mediterranean forest trees (MFO). The VPIFs spectral band correction factors (CFs) to implement the ARIN linear normalization procedure largely varied among spectral bands for any given image and among images for any given spectral band. The correlation coefficients between the CFs among VPIFs for any spectral band and overall all bands are over 0.83 and significant at P=0.95 or higher. For the ARIN normalized images, the range and standard deviation of any spectral bands and vegetation indices values were considerably reduced as compared to the original images, regardless the VPIF or the combination of VPIFs selected for normalization, which proves the method efficacy. Moreover, ARIN method was easier and efficient than the absolute calibration QUAC method, and somehow similarly efficient as the highly tunable FLAASH, in which solar position and weather calibration parameters are required.
Descripción Trabajo presentado en el SPIE Remote Sensing, celebrado en Dresden (Alemania) del 23 al 26 de septiembre de 2013.
URI http://hdl.handle.net/10261/96004
ReferenciasGarcía Torres, Luis. ARIN software para la normalización automática de imágenes remotas multi-temporales en base a usos de suelo vegetales pseudo-invariantes. http://hdl.handle.net/10261/120824
García-Torres, Luis, Caballero Novella, Juan José, Gómez-Candón, David, Castro, Ana Isabel de. Semi-automatic normalization of multitemporal remote images based on vegetative pseudo-invariant features. http://dx.doi.org/10.1371/journal.pone.0091275 . http://hdl.handle.net/10261/101191
Caballero Novella, Juan José, García-Torres, Luis, Gómez-Candón, David. Procedimiento ARIN para la normalización de imágenes remotas multitemporales mediante el uso de cultivos pseudo-invariantes. https://digital.csic.es/handle/10261/121190
García Torres, Luis; Caballero Novella, Juan José; Gómez-Candón, David; Peña Barragán, José Manuel; López Granados, Francisca. Procedimiento para la normalización automática de imágenes remotas multitemporales en base a usos de suelo pseudo-invariantes vegetales. http://hdl.handle.net/10261/120835
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